A multi-aspect online tuning framework for HPC applications

Michael Gerndt, Siegfried Benkner, Eduardo César, Carmen Navarrete, Enes Bajrovic, Jiri Dokulil, Carla Guillén, Robert Mijakovic, Anna Sikora

Research output: Contribution to journalArticleResearchpeer-review

Abstract

© 2017, Springer Science+Business Media New York. Developing software applications for high-performance computing (HPC) requires careful optimizations targeting a myriad of increasingly complex, highly interrelated software, hardware and system components. The demands placed on minimizing energy consumption on extreme-scale HPC systems and the associated shift towards hete rogeneous architectures add yet another level of complexity to program development and optimization. As a result, the software optimization process is often seen as daunting, cumbersome and time-consuming by software developers wishing to fully exploit HPC resources. To address these challenges, we have developed the Periscope Tuning Framework (PTF), an online automatic integrated tuning framework that combines both performance analysis and performance tuning with respect to the myriad of tuning parameters available to today’s software developer on modern HPC systems. This work introduces the architecture, tuning model and main infrastructure components of PTF as well as the main tuning plugins of PTF and their evaluation.
Original languageEnglish
Pages (from-to)1063-1096
JournalSoftware Quality Journal
Volume26
Issue number3
DOIs
Publication statusPublished - 1 Sep 2018

Keywords

  • Automatic performance tuning
  • Energy tuning
  • High-performance computing
  • OpenCL
  • Parallel architectures
  • Performance optimization

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  • Cite this

    Gerndt, M., Benkner, S., César, E., Navarrete, C., Bajrovic, E., Dokulil, J., Guillén, C., Mijakovic, R., & Sikora, A. (2018). A multi-aspect online tuning framework for HPC applications. Software Quality Journal, 26(3), 1063-1096. https://doi.org/10.1007/s11219-017-9370-x